#To load image with all the analyses below done

Ploting

Engrams + NE together

2D

3D

Quantify

ANOVA with euclidean distances

##     Group infected    N euclidean_distance       sd         se        ci
## 1  AD_GFP      Neg 3793           7.039275 3.716410 0.06034374 0.1183093
## 2  AD_GFP      Pos 1532           4.684451 3.872973 0.09894983 0.1940915
## 3  AD_OSK      Neg 4417           7.482256 3.657594 0.05503409 0.1078944
## 4  AD_OSK      Pos 1213           4.723786 3.847787 0.11047922 0.2167518
## 5 CON_GFP      Neg 4545           6.853849 3.592678 0.05329069 0.1044757
## 6 CON_GFP      Pos 1562           4.163874 3.009446 0.07614581 0.1493589
##                   Df Sum Sq Mean Sq  F value Pr(>F)    
## infected           1  22100   22100 1674.143 <2e-16 ***
## Group              2   1116     558   42.273 <2e-16 ***
## infected:Group     2     99      49    3.745 0.0237 *  
## Residuals      17056 225149      13                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = euclidean_distance ~ infected * Group, data = cell_meta_2)
## 
## $infected
##              diff       lwr       upr p adj
## Pos-Neg -2.619871 -2.745376 -2.494365     0
## 
## $Group
##                      diff        lwr        upr     p adj
## AD_OSK-AD_GFP   0.3368662  0.1740759  0.4996566 0.0000037
## CON_GFP-AD_GFP -0.2796102 -0.4392803 -0.1199400 0.0001205
## CON_GFP-AD_OSK -0.6164764 -0.7738192 -0.4591336 0.0000000
## 
## $`infected:Group`
##                                diff        lwr        upr     p adj
## Pos:AD_GFP-Neg:AD_GFP   -2.35482376 -2.6682857 -2.0413619 0.0000000
## Neg:AD_OSK-Neg:AD_GFP    0.44298183  0.2137567  0.6722069 0.0000006
## Pos:AD_OSK-Neg:AD_GFP   -2.31548856 -2.6570504 -1.9739267 0.0000000
## Neg:CON_GFP-Neg:AD_GFP  -0.18542560 -0.4131546  0.0423034 0.1856914
## Pos:CON_GFP-Neg:AD_GFP  -2.87540045 -3.1867108 -2.5640901 0.0000000
## Neg:AD_OSK-Pos:AD_GFP    2.79780558  2.4907799  3.1048312 0.0000000
## Pos:AD_OSK-Pos:AD_GFP    0.03933519 -0.3586411  0.4373114 0.9997623
## Neg:CON_GFP-Pos:AD_GFP   2.16939816  1.8634879  2.4753084 0.0000000
## Pos:CON_GFP-Pos:AD_GFP  -0.52057669 -0.8929135 -0.1482398 0.0009585
## Pos:AD_OSK-Neg:AD_OSK   -2.75847039 -3.0941352 -2.4228055 0.0000000
## Neg:CON_GFP-Neg:AD_OSK  -0.62840743 -0.8471924 -0.4096224 0.0000000
## Pos:CON_GFP-Neg:AD_OSK  -3.31838227 -3.6232109 -3.0135536 0.0000000
## Neg:CON_GFP-Pos:AD_OSK   2.13006296  1.7954180  2.4647079 0.0000000
## Pos:CON_GFP-Pos:AD_OSK  -0.55991188 -0.9561957 -0.1636281 0.0008052
## Pos:CON_GFP-Neg:CON_GFP -2.68997485 -2.9936801 -2.3862696 0.0000000
##               Df Sum Sq Mean Sq F value   Pr(>F)    
## Group          2    289  144.57    11.3 1.27e-05 ***
## Residuals   4304  55047   12.79                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = euclidean_distance ~ Group, data = cell_meta_pos)
## 
## $Group
##                       diff        lwr        upr     p adj
## AD_OSK-AD_GFP   0.03933519 -0.2829154  0.3615858 0.9558587
## CON_GFP-AD_GFP -0.52057669 -0.8220664 -0.2190869 0.0001553
## CON_GFP-AD_OSK -0.55991188 -0.8807920 -0.2390317 0.0001295

MANOVA

##              Df   Wilks approx F num Df den Df    Pr(>F)    
## Condition     5 0.93352   79.194     15  47079 < 2.2e-16 ***
## Residuals 17056                                             
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## $`Pos.AD_OSK vs Pos.CON_GFP`
##             Df   Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.98853   10.713      3   2771 5.338e-07 ***
## Residuals 2773                                             
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $`Pos.AD_OSK vs Pos.AD_GFP`
##             Df   Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.98318   15.635      3   2741 4.402e-10 ***
## Residuals 2743                                             
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $`Pos.AD_OSK vs Neg.AD_OSK`
##             Df   Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.94247   114.47      3   5626 < 2.2e-16 ***
## Residuals 5628                                             
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $`Pos.AD_OSK vs Neg.CON_GFP`
##             Df   Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.96179   76.195      3   5754 < 2.2e-16 ***
## Residuals 5756                                             
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $`Pos.AD_OSK vs Neg.AD_GFP`
##             Df   Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.96471   60.986      3   5002 < 2.2e-16 ***
## Residuals 5004                                             
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $`Pos.CON_GFP vs Pos.AD_GFP`
##             Df  Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.9521   51.822      3   3090 < 2.2e-16 ***
## Residuals 3092                                            
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $`Pos.CON_GFP vs Neg.AD_OSK`
##             Df   Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.92461   162.39      3   5975 < 2.2e-16 ***
## Residuals 5977                                             
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $`Pos.CON_GFP vs Neg.CON_GFP`
##             Df   Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.94729   113.19      3   6103 < 2.2e-16 ***
## Residuals 6105                                             
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $`Pos.CON_GFP vs Neg.AD_GFP`
##             Df   Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.94466   104.48      3   5351 < 2.2e-16 ***
## Residuals 5353                                             
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $`Pos.AD_GFP vs Neg.AD_OSK`
##             Df   Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.90591   205.82      3   5945 < 2.2e-16 ***
## Residuals 5947                                             
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $`Pos.AD_GFP vs Neg.CON_GFP`
##             Df   Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.94028   128.56      3   6073 < 2.2e-16 ***
## Residuals 6075                                             
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $`Pos.AD_GFP vs Neg.AD_GFP`
##             Df  Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.9355   122.28      3   5321 < 2.2e-16 ***
## Residuals 5323                                            
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $`Neg.AD_OSK vs Neg.CON_GFP`
##             Df   Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.99211   23.751      3   8958 2.638e-15 ***
## Residuals 8960                                             
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $`Neg.AD_OSK vs Neg.AD_GFP`
##             Df   Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.99275   19.978      3   8206 6.744e-13 ***
## Residuals 8208                                             
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## $`Neg.CON_GFP vs Neg.AD_GFP`
##             Df   Wilks approx F num Df den Df    Pr(>F)    
## Condition    1 0.98926   30.158      3   8334 < 2.2e-16 ***
## Residuals 8336                                             
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

3D density

Only positive

CON: Grey AD: Blue AD OSK: Green

RNA_identity + AD_Engram

AD_Engram + Engram

Compare positive and negative

Positive: Grey Negative: Red

RNA_identity + AD_Engram

AD_Engram + Engram

Engrams

2D

### 3D

Non engrams

2D

Quantification

Cell identity

##     Group infected    N RNA_identity_score         sd           se          ci
## 1  AD_GFP      Neg 3793          0.5383472 0.06338481 0.0010291857 0.002017811
## 2  AD_GFP      Pos 1532          0.5300116 0.06206719 0.0015857425 0.003110457
## 3  AD_OSK      Neg 4417          0.5386765 0.06307698 0.0009490895 0.001860691
## 4  AD_OSK      Pos 1213          0.5403867 0.05938564 0.0017051045 0.003345284
## 5 CON_GFP      Neg 4545          0.5293344 0.07653628 0.0011352732 0.002225687
## 6 CON_GFP      Pos 1562          0.5434752 0.06571780 0.0016628096 0.003261576
##                   Df Sum Sq Mean Sq F value   Pr(>F)    
## infected           1   0.02 0.02121   4.739   0.0295 *  
## Group              2   0.11 0.05635  12.589 3.44e-06 ***
## infected:Group     2   0.29 0.14298  31.946 1.42e-14 ***
## Residuals      17056  76.34 0.00448                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = RNA_identity_score ~ infected * Group, data = cell_meta)
## 
## $infected
##                diff          lwr         upr     p adj
## Pos-Neg 0.002566697 0.0002557277 0.004877665 0.0294939
## 
## $Group
##                        diff           lwr           upr     p adj
## AD_OSK-AD_GFP   0.003281368  0.0002838615  6.278875e-03 0.0277973
## CON_GFP-AD_GFP -0.002915924 -0.0058559786  2.412974e-05 0.0524836
## CON_GFP-AD_OSK -0.006197293 -0.0090944921 -3.300093e-03 0.0000016
## 
## $`infected:Group`
##                                  diff           lwr          upr     p adj
## Pos:AD_GFP-Neg:AD_GFP   -0.0083355544 -0.0141074213 -0.002563688 0.0005534
## Neg:AD_OSK-Neg:AD_GFP    0.0003293357 -0.0038914545  0.004550126 0.9999259
## Pos:AD_OSK-Neg:AD_GFP    0.0020395119 -0.0042497677  0.008328792 0.9404157
## Neg:CON_GFP-Neg:AD_GFP  -0.0090128413 -0.0132060829 -0.004819600 0.0000000
## Pos:CON_GFP-Neg:AD_GFP   0.0051280059 -0.0006042439  0.010860256 0.1101079
## Neg:AD_OSK-Pos:AD_GFP    0.0086648901  0.0030115357  0.014318244 0.0001829
## Pos:AD_OSK-Pos:AD_GFP    0.0103750664  0.0030470117  0.017703121 0.0007780
## Neg:CON_GFP-Pos:AD_GFP  -0.0006772869 -0.0063101033  0.004955530 0.9993798
## Pos:CON_GFP-Pos:AD_GFP   0.0134635603  0.0066076115  0.020319509 0.0000004
## Pos:AD_OSK-Neg:AD_OSK    0.0017101763 -0.0044705200  0.007890873 0.9695410
## Neg:CON_GFP-Neg:AD_OSK  -0.0093421770 -0.0133707304 -0.005313623 0.0000000
## Pos:CON_GFP-Neg:AD_OSK   0.0047986702 -0.0008142306  0.010411571 0.1437575
## Neg:CON_GFP-Pos:AD_OSK  -0.0110523533 -0.0172142695 -0.004890437 0.0000048
## Pos:CON_GFP-Pos:AD_OSK   0.0030884939 -0.0042083975  0.010385385 0.8340025
## Pos:CON_GFP-Neg:CON_GFP  0.0141408472  0.0085486329  0.019733062 0.0000000
##               Df Sum Sq Mean Sq F value   Pr(>F)    
## Group          2  0.151 0.07568   19.26 4.72e-09 ***
## Residuals   4304 16.914 0.00393                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = RNA_identity_score ~ Group, data = cell_meta_pos)
## 
## $Group
##                       diff          lwr         upr     p adj
## AD_OSK-AD_GFP  0.010375066  0.004726344 0.016023788 0.0000505
## CON_GFP-AD_GFP 0.013463560  0.008178754 0.018748366 0.0000000
## CON_GFP-AD_OSK 0.003088494 -0.002536206 0.008713194 0.4023676

Engram score

##     Group infected    N   Engram       sd         se        ci
## 1  AD_GFP      Neg 3793 11.46841 6.881428 0.11173446 0.2190654
## 2  AD_GFP      Pos 1532 12.97797 5.113672 0.13064822 0.2562684
## 3  AD_OSK      Neg 4417 11.26788 7.147655 0.10754740 0.2108468
## 4  AD_OSK      Pos 1213 13.49662 5.194060 0.14913397 0.2925894
## 5 CON_GFP      Neg 4545 11.93334 6.681481 0.09910733 0.1942986
## 6 CON_GFP      Pos 1562 14.42729 4.390256 0.11108344 0.2178885
##                   Df Sum Sq Mean Sq F value   Pr(>F)    
## infected           1  13997   13997 335.851  < 2e-16 ***
## Group              2   2131    1065  25.563 8.22e-12 ***
## infected:Group     2    575     288   6.902  0.00101 ** 
## Residuals      17056 710850      42                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Engram ~ infected * Group, data = cell_meta)
## 
## $infected
##             diff      lwr      upr p adj
## Pos-Neg 2.085023 1.862017 2.308029     0
## 
## $Group
##                       diff        lwr      upr     p adj
## AD_OSK-AD_GFP  -0.00400414 -0.2932603 0.285252 0.9994197
## CON_GFP-AD_GFP  0.73508653  0.4513745 1.018799 0.0000000
## CON_GFP-AD_OSK  0.73909067  0.4595141 1.018667 0.0000000
## 
## $`infected:Group`
##                               diff         lwr        upr     p adj
## Pos:AD_GFP-Neg:AD_GFP    1.5095699  0.95259097  2.0665488 0.0000000
## Neg:AD_OSK-Neg:AD_GFP   -0.2005265 -0.60782815  0.2067752 0.7251985
## Pos:AD_OSK-Neg:AD_GFP    2.0282157  1.42130706  2.6351244 0.0000000
## Neg:CON_GFP-Neg:AD_GFP   0.4649387  0.06029543  0.8695820 0.0135381
## Pos:CON_GFP-Neg:AD_GFP   2.9588814  2.40572547  3.5120373 0.0000000
## Neg:AD_OSK-Pos:AD_GFP   -1.7100963 -2.25563891 -1.1645538 0.0000000
## Pos:AD_OSK-Pos:AD_GFP    0.5186459 -0.18850347  1.2257952 0.2922958
## Neg:CON_GFP-Pos:AD_GFP  -1.0446312 -1.58819186 -0.5010705 0.0000007
## Pos:CON_GFP-Pos:AD_GFP   1.4493115  0.78771986  2.1109031 0.0000000
## Pos:AD_OSK-Neg:AD_OSK    2.2287422  1.63231171  2.8251727 0.0000000
## Neg:CON_GFP-Neg:AD_OSK   0.6654652  0.27671412  1.0542162 0.0000160
## Pos:CON_GFP-Neg:AD_OSK   3.1594078  2.61776898  3.7010467 0.0000000
## Neg:CON_GFP-Pos:AD_OSK  -1.5632770 -2.15789529 -0.9686588 0.0000000
## Pos:CON_GFP-Pos:AD_OSK   0.9306656  0.22652350  1.6348077 0.0022914
## Pos:CON_GFP-Neg:CON_GFP  2.4939427  1.95430003  3.0335853 0.0000000
##               Df Sum Sq Mean Sq F value   Pr(>F)    
## Group          2   1664   832.1   34.83 9.88e-16 ***
## Residuals   4304 102820    23.9                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Engram ~ Group, data = cell_meta_pos)
## 
## $Group
##                     diff        lwr       upr     p adj
## AD_OSK-AD_GFP  0.5186459 0.07822606 0.9590657 0.0159594
## CON_GFP-AD_GFP 1.4493115 1.03726548 1.8613575 0.0000000
## CON_GFP-AD_OSK 0.9306656 0.49211874 1.3692125 0.0000021

AD (Engram) score

##     Group infected    N       AD       sd         se        ci
## 1  AD_GFP      Neg 3793 6.245809 3.945846 0.06406911 0.1256132
## 2  AD_GFP      Pos 1532 6.616369 2.711663 0.06927975 0.1358933
## 3  AD_OSK      Neg 4417 5.975718 4.218301 0.06347078 0.1244345
## 4  AD_OSK      Pos 1213 5.992133 3.000105 0.08614022 0.1690005
## 5 CON_GFP      Neg 4545 5.764117 3.904469 0.05791553 0.1135426
## 6 CON_GFP      Pos 1562 5.454999 2.669654 0.06754832 0.1324950
##                   Df Sum Sq Mean Sq F value   Pr(>F)    
## infected           1      5     4.8   0.343    0.558    
## Group              2   1264   632.1  44.890  < 2e-16 ***
## infected:Group     2    260   130.0   9.233 9.83e-05 ***
## Residuals      17056 240183    14.1                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = AD ~ infected * Group, data = cell_meta)
## 
## $infected
##               diff         lwr       upr     p adj
## Pos-Neg 0.03873784 -0.09089024 0.1683659 0.5580486
## 
## $Group
##                      diff        lwr        upr    p adj
## AD_OSK-AD_GFP  -0.3703652 -0.5385029 -0.2022275 8.00e-07
## CON_GFP-AD_GFP -0.6661286 -0.8310437 -0.5012135 0.00e+00
## CON_GFP-AD_OSK -0.2957634 -0.4582746 -0.1332522 5.95e-05
## 
## $`infected:Group`
##                                diff         lwr          upr     p adj
## Pos:AD_GFP-Neg:AD_GFP    0.37056032  0.04680173  0.694318914 0.0141208
## Neg:AD_OSK-Neg:AD_GFP   -0.27009051 -0.50684530 -0.033335731 0.0146296
## Pos:AD_OSK-Neg:AD_GFP   -0.25367538 -0.60645696  0.099106203 0.3143989
## Neg:CON_GFP-Neg:AD_GFP  -0.48169151 -0.71690103 -0.246481998 0.0000001
## Pos:CON_GFP-Neg:AD_GFP  -0.79080993 -1.11234630 -0.469273557 0.0000000
## Neg:AD_OSK-Pos:AD_GFP   -0.64065083 -0.95776176 -0.323539908 0.0000002
## Pos:AD_OSK-Pos:AD_GFP   -0.62423570 -1.03528479 -0.213186607 0.0002190
## Neg:CON_GFP-Pos:AD_GFP  -0.85225183 -1.16821073 -0.536292931 0.0000000
## Pos:CON_GFP-Pos:AD_GFP  -1.16137025 -1.54593773 -0.776802764 0.0000000
## Pos:AD_OSK-Neg:AD_OSK    0.01641513 -0.33027573  0.363106001 0.9999938
## Neg:CON_GFP-Neg:AD_OSK  -0.21160100 -0.43757274  0.014370742 0.0816237
## Pos:CON_GFP-Neg:AD_OSK  -0.52071941 -0.83556120 -0.205877628 0.0000361
## Neg:CON_GFP-Pos:AD_OSK  -0.22801613 -0.57365358  0.117621316 0.4144369
## Pos:CON_GFP-Pos:AD_OSK  -0.53713455 -0.94643562 -0.127833475 0.0025411
## Pos:CON_GFP-Neg:CON_GFP -0.30911842 -0.62279984  0.004563012 0.0561362
##               Df Sum Sq Mean Sq F value Pr(>F)    
## Group          2   1044   522.2   67.51 <2e-16 ***
## Residuals   4304  33292     7.7                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = AD ~ Group, data = cell_meta_pos)
## 
## $Group
##                      diff        lwr        upr   p adj
## AD_OSK-AD_GFP  -0.6242357 -0.8748444 -0.3736270 1.0e-07
## CON_GFP-AD_GFP -1.1613702 -1.3958336 -0.9269069 0.0e+00
## CON_GFP-AD_OSK -0.5371345 -0.7866775 -0.2875916 1.4e-06

#Save image